What to Expect: - AWS Lambda concepts - Common Serverless use cases - Monolithic vs. service oriented architecture - Debugging applications with AWS Cloudwatch and AWS X-Ray

2. WIFI: awsDevDay | PASS: CodeHappy
U P N E X T :
Distributed Serverless Stack
Tracing and Monitoring

3. T H A N K S T O O U R F R I E N D S A T :

4. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Kashif Imran, Sr. Solutions Architect AWS
10/10/2017
Distributed Serverless Stack
Tracing and Monitoring

5. What to expect from the session
• Overview
• Use cases
• API
• Getting started
• Demo

6. AWS Lambda Concepts

7. Serverless means…
No servers to provision
or manage
Scales with usage
Never pay for idle Availability and fault
tolerance built in

8. Never pay for Idle
EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE

9. Amazon S3 Amazon
DynamoDB
Amazon
Kinesis
AWS
CloudFormation
AWS
CloudTrail
Amazon
CloudWatch
Amazon SNSAmazon
SES
Amazon
API Gateway
Amazon
Cognito
AWS
IoT
Amazon
Alexa
Cron events
DATA STORES ENDPOINTS
REPOSITORIES EVENT/MESSAGE SERVICES
Event Sources that integrate with AWS Lambda
… and the list will continue to grow!
Amazon RDS
Aurora

10. Common Serverless Use Cases
Web
Applications
• Static websites
• Complex web
apps
• Packages for
Flask and
Express
Data
Processing
• Real time
• MapReduce
• Batch
Chatbots
• Powering
chatbot logic
Backends
• Apps &
services
• Mobile
• IoT
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Amazon
Alexa
• Powering
voice-enabled
apps
• Alexa Skills
Kit
Autonomous
IT
• Policy engines
• Extending
AWS services
• Infrastructure
management

11. Monolithic
Monolithic vs. Service Oriented Architecture
Service Oriented Architecture

12. Drawbacks of Monolithic Architecture
Hard to Iterate Fast CI/CD Time ConsumingHard to scale Efficiently
Reliability Challenges

13. Benefits of Service Oriented Architecture
Increased Agility Easy to Scale Improved Innovation
Reduced Human Errors

14. Debugging applications

15. Traditional Debugging
Developer Local Test
Developer
Add
Breakpoints
Add Log
Statements

16. The traditional process of debugging doesn’t scale well for
production applications or those built using a service-
oriented, microservice, or serverless architecture
It’s tedious, repetitive, and time consuming.

17. Debug Lambda with CloudWatch

18. Debug Lambda with CloudWatch…

19. Debug Lambda with CloudWatch…

20. Debugging applications with X-Ray

21. Identify Performance
Bottlenecks
How does AWS X-Ray help?
Pinpoint Specific
Service Issues
Identify Errors Identify Impact to
Users

22. How X-Ray works

23. Use cases

24. Visualize service call graph

25. Lambda on the AWS X-Ray Service Map

26. Identify impact

27. Identify performance bottlenecks

28. Identify performance bottlenecks

29. Identify performance bottlenecks

30. Pinpoint issues

31. Pinpoint issues

32. Pinpoint issues

33. AWS X-Ray Concepts

34. X-Ray Key Concepts
Trace End-to-end data related a single request across services
Segments Portions of the trace that correspond to a single service
Sub-segments Remote call or local compute sections within a service
Annotations Business data that can be used to filter traces
Metadata Business data that can be added to the trace but not used
for filtering traces
Errors Normalized error message and stack trace
Sampling Percentage of requests to your application to capture as
traces

35. X-Ray SDK
Available for Java, .NET, and Node.js
Adds filters to automatically captures metadata for calls to:
• AWS services using the AWS SDK
• Non-AWS services over HTTP and HTTPS
• Databases (MySQL, PostgreSQL, and Amazon DynamoDB)
• Queues (Amazon SQS)
Enables you to get started quickly without having to manually
instrument your application code to log metadata about requests

36. X-Ray Daemon
Receives data from the SDK over UDP and acts as a local buffer.
Data is flushed to the backend every second or when the local
buffer fills.
Available for Amazon Linux AMI, RHEL, Ubuntu, OS X, and
Windows.
Can be run anywhere as long as AWS credentials are provided
(e.g.: EC2, ECS, on premise, developer machine, etc.)

37. Sampling configuration
{
"rules": {
"move": {
"id": 1,
"service_name": "*",
"http_method": "*",
"url_path": "/api/move/*",
"fixed_target": 0,
"rate": 0.05
},
"base": {
"id": 2,
"service_name": "*",
"http_method": "*",
"url_path": "*",
"fixed_target": 1,
"rate": 0.1
}
}
}
This example defines two rules.
The first rule applies a five-percent sampling rate
with no minimum number of requests to trace to
requests with paths under /api/move
The second overrides the default sampling rule
with a rule that traces the first request each
second and 10 percent of additional requests.

38. AWS X-Ray API

39. X-Ray API
Raw trace data is available using batch get APIs.
X-Ray provides a set of APIs to enable you to send, filter, and retrieve
trace data.
You can send trace data directly to the service without having to use
our SDKs. (e.g. you can write your own SDKs for languages/frameworks not currently supported)
You can build your own data analysis applications on top of the data
collected by X-Ray.

40. X-Ray API
PutTraceSegments Uploads segment documents to AWS X-Ray
BatchGetTraces Retrieves a list of traces specified by ID
GetServiceGraph Retrieves a document that describes services in your
application and their connections
GetTraceSummaries Retrieves IDs and metadata for traces available for a
specified time frame using an optional filter

41. Segment document
Minimal example
{
"name" : "example.com",
"id" : "70de5b6f19ff9a0a",
"start_time" : 1.478293361271E9,
"trace_id" : "1-581cf771-a006649127e371903a2de979",
"end_time" : 1.478293361449E9
}
Example showing an in-progress segment
{
"name" : "example.com",
"id" : "70de5b6f19ff9a0b",
"start_time" : 1.478293361271E9,
"trace_id" : "1-581cf771-a006649127e371903a2de979",
“in_progress”: true
}

42. Getting started

43. Agent installation (Amazon Linux)
#!/bin/bash
curl https://s3.dualstack.us-east-1.amazonaws.com/aws-xray-assets.us-east-1/xray-daemon/aws-xray-
daemon-1.x.rpm -o /home/ec2-user/xray.rpm
yum install -y /home/ec2-user/xray.rpm

44. Agent Installation (Windows)

45. Agent installation (Amazon ECS)

46. Enable X-Ray in AWS Lambda

47. Application instrumentation (Node.js)
Example pseudo code:

48. Demo

49. Pricing

50. X-Ray pricing
Free during the preview. After that:
Free tier
• The first 100,000 traces recorded per month are free
• The first 1,000,000 traces retrieved or scanned per month are free
Additional charges
• Beyond the free tier, traces recorded cost $5.00 per million per month
• Beyond the free tier, traces retrieved or scanned cost $0.50 per million per
month

51. Available Today!
The AWS X-Ray service is available today.
Go to https://aws.amazon.com/xray to get started.
Documentation: http://docs.aws.amazon.com/xray/latest/devguide/aws-xray.html
.NET Sample: https://github.com/awslabs/aws-xray-dotnet-webapp
Java Sample: https://github.com/awslabs/eb-java-scorekeep/tree/xray
Node.js Sample: https://github.com/awslabs/eb-node-express-sample/tree/xray

52. Thank You!

53. Don’t Forget Evaluations!